Method for dynamically delivering contents encapsulated with capsule overviews corresonding to the plurality of documents, resolving co-referentiality related to frequency within document, determining topic stamps for each document segments

ABSTRACT

A method for the dynamic presentation of the contents of a plurality of documents on a display is disclosed. The method comprises receiving a plurality of documents and providing a plurality of topically rich capsule overviews corresponding to the plurality of documents. The method also includes dynamically delivering document content encapsulated in the plurality of capsule overviews. In so doing, the method in accordance with the present invention can present thematic capsule overviews of the documents to users. The capsule overviews, delivered in a variety of dynamic presentation modes, allow the user to quickly get a sense of what a document is about, and decide whether they want to read it in more detail. In a preferred embodiment, the capsule overviews include a containment hierarchy which relates the different information levels in a document together, and which includes a collection of highly salient topic stamps embedded in layers of progressively richer and more informative contextualized text fragments. The novel presentation metaphors which the invention utilizes are based on notions of temporal typography, in particular for exploiting the interactions between form and content.

CROSS-REFERENCE TO RELATED APPLICATIONS

The present application is a continuation application of applicationSer. No. 08/972,935, is now U.S. Pat. No. 6,353,824 entitled “METHOD FORDYNAMIC REPRESENTATION OF THE CONTENTS OF TOPICALLY RICH CAPSULEOVERVIEWS CORRESPONDING TO A PLURALITY OF DOCUMENTS, RESOLVINGCO-REFERENTIALITY IN DOCUMENT SEGMENTS,” filed on Nov. 18, 1997 andassigned to the same Assignee as the present application.

FIELD OF THE INVENTION

The present invention relates generally to a system and method forreviewing documents. More particularly, the present invention relates topresentation of documents in a manner that allows the user to quicklyascertain their contents.

BACKGROUND OF THE INVENTION

Documents obtained via an electronic medium (i.e., the Internet oron-line services, such as AOL, Compuserve or other services) are oftenprovided in such volume that it is important to be able to summarizethem. Oftentimes, it is desired to be able to quickly obtain a brief(i.e., a few sentences or a paragraph length) summary of the documentrather than reading it in its completeness. Most typically, suchdocuments span several paragraphs to several pages in length. Thepresent invention concerns itself with this kind of document,hereinafter referred to as average length document.

Present day summarization technologies fall short of delivering fillyinformative summaries of documents. To some extent, this is so becauseof shortcomings of the state-of-the-art in natural language processing;in general, the issue of how to customize a summarization procedure fora specific information seeking task is still an open one. However, giventhe rapidly growing volume of document-based information on-line, theneed for any kind of document abstraction mechanism is so great thatsummarization technologies are beginning to get deployed in real worldsituations.

The majority of techniques for “summarization”, as applied toaverage-length documents, fall within two broad categories. A class oftechniques mine a document for certain pre-specified pieces ofinformation, typically defined a priori, on the basis of fixing the mostcharacteristic features of a known domain of interest. Other approachesrely, in effect, on ‘re-using’ certain fragments of the original text;these have been identified, typically by some-similarity metric, asclosest in meaning to the whole document. This categorization is not arigid one: a number of approaches (as exhibited, for instance, in arecent workshop on Association for Computational Linguistics,“Proceedings of a Workshop on Intelligent, Scalable, TextSummarization,” Madrid, Spain, 1997) use strong notions of topicality(B. Boguraev and C. Kennedy, “Salience-based content characterization oftext documents,” in Proceedings of ACL '97 Workshop on Intelligent,Scalable Text Summarization, Madrid, Spain, 1997), (E. Hovy and C. Y.Lin, “Automated text summarization in SUMMARIST,” in Proceedings of ACL'97 Workshop on Intelligent, Scalable Text Summarization, Madrid, Spain,1997), lexical chains (R. Barzilay and M. Elhadad, “Using lexical chainsfor text summarization,” in Proceedings of ACL '97 Workshop onIntelligent, Scalable Text Summarization, Madrid, Spain, 1997), anddiscourse structure (D. Marcu, “From discourse structures to textsummaries”, in Proceedings of ACL '97 Workshop on Intelligent, ScalableText Summarization, Madrid, Spain, 1997), (U. Hahn and M. Strube,“Centered segmentation: scaling up the centering model to globaldiscourse structure,” in Proceedings of ACL-EACL/97, 35th Annual Meetingof the Association for Computational Linguistics and 8th Conference ofthe European Chapter of the Association for Computational Linguistics,Madrid, Spain, 1997), thus laying claim to newer sets of methods.

Still, at a certain level of abstraction, all approaches share afundamental similarity: summarization methods today rely, in essence, onsubstantial data reduction over the original document source. Such aposition leads to several usability questions.

Given the extracted fragments which any particular method has identifiedas worth preserving, what is an optimal way of encapsulating these intoa coherent whole, for presenting to the user? Acknowledging thatdifferent information management tasks may require different kinds ofsummary, even from the same document, how should the data discarded bythe reduction process be retained, in case a reference is necessary to apart of the document not originally included, in the summary? What arethe trade-offs in fixing the granularity of analysis: for instance, aresentences better than paragraphs as information-bearing passages, or arephrases even better? Of particular importance to this invention is thequestion of “user involvement.” From the end-user's point of view,making judgements, on the basis of a summary, concerning what a documentis about and whether to pay it closer attention would engage the user ina sequence of actions: look at the summary, absorb its semantic impact,infer what the document might be about, decide whether to consult thesource, somehow call up the full document, and navigate to the point(s)of interest. Given that this introduces a serious amount of cognitiveand operational overhead, what are the implications for the user whenthey are faced with a large, and growing, number of documents to dealwith on a daily basis?

These are only some of the questions concerning the acceptability ofsummarization technology by end users. There is particular urgency,given the currently evolving notion of “infornmation push”, wherecontent arriving unsolicited, and in large quantities, at individualworkstations threatens users with real and immediate informationoverload. To the extent that broad coverage summarization techniques arebeginning to get deployed in real world situations, it is still the casethat these techniques are based primarily on sentence extractionmethods. In such a context, the above questions take on more specificinterpretations. Thus, is it appropriate to concatenate together thesentences extracted as representative—especially when they come fromdisjoint parts of the source document? What could be done, within asentence extraction framework, to ensure that all ‘themes’ in a documentget represented by the set of sentences identified by the technology?How can the jarring effect of ‘dangling’ (and unresolved) references inthe selection—without any obvious means of identifying the referents inthe original text—be overcome? What mechanisms could be developed foroffering the user additional information from the document, for morefocused attention to detail? What is the value of the sentence, as abasic information-bearing unit, as a window into a multi-document space?

To illustrate some of these issues, consider several examples from anoperational news tracking site: the News Channel page of Excite, aninformation vendor and a popular search engine host for the World WideWeb, which is available via the “Ongoing Coverage” section of the newstracking page, (http://nt.excite.com). Under the heading of Articlesabout IRS Abuses Alleged, some entries read:

EXAMPLE 1

RENO ON Sunday/Reform Taxes the . . .

The problem, of course, is that the enemies of the present system areall grinding different axes. How true, how true, and ditto for most ofthe people who sit on the Finance Committee. (First found: Oct. 18,1997)

EXAMPLE 2

Scheduled IRS Layoffs For 500 Are . . .

The Agency's original plan called for eliminating as many as 5,000 jobsin field offices and at the Washington headquarters. “The way this hasturned out, it works to the agency's advantage, the employees' advantageand the union's advantage.” (First found: Oct. 17, 1997.)

Both examples present summaries as sentences which almost seamlesslyfollow one another. While this may account for acceptable readability,it is at best misleading, as in the original documents these sentencesare several paragraphs apart. This makes it hard to know that thereferences to “How true, how true”, in the first example, and “The waythis has turned out”, in the second, are not whatever might be mentionedin the preceding summary sentences, but are, in fact, hidden somewherein the original text of the documents. Opening references to “Theproblem” and “the agency” are hard to resolve. The thrust of the secondarticle—namely that there is a reversal of an anticipated situation—isnot at all captured: it turns out that the missing paragraphs betweenthe summary sentences discuss how the planned 5,000 layoffs have beenreduced to “4,000, then 1,400 and finally settled at about 500”, andthat “now, even those 500 workers will not be cut”. As it turns out,some indication to this effect might have been surmised from the fulltitle of the article, Scheduled IRS Layoffs For 500 Are Canceled;unfortunately, this has been truncated by a data reduction strategywhich is insensitive to notions of linguistic phrases, auxiliary verbconstructions, mood, and so forth.

In the extreme case, such summaries can range from under-informative (asillustrated by the first example above), to misleading (the secondexample), to plainly devoid of any useful information. Another examplefrom the same site reads:

EXAMPLE 3

Technology News from Wired News

This is more than 500 times thinner than a human hair.

“Don't expect one in a present under your Christmas tree this year.”

Accordingly, a particular problem that must be addressed is how to “fillin the gaps” which the data reduction process necessarily introduces asa summary is constructed by choosing certain fragments from the originalsource. Presently, known ways for filling such gaps, assuming of coursethese are even perceived, is by the active user involvement ofrequesting the entire document.

Currently, there is a relatively rigid mechanism typically sensitive toa mouse click, or some similar interactive command, with the simplesemantics of “bring up the entire document, possibly with the point ofview focused on the particular sentence of the summary which receivedthe click, presented in its natural document context, and maybehighlighted”. Clearly, having a richer data structure would facilitategreater flexibility in interactions with what would be, in effect, awhole range of dynamically reconfigured summaries at different level ofgranularity and detail.

There is still one problem, however: the process of filling in the gapsrequires active user involvement. In principle there is nothing wrongwith this. In practice, real information management environments involveworking with a large number of documents. It is far from clear thatusers will have the energy, bandwidth, dedication, and concentrationrequired to assess, absorb, and act upon summaries for each one of thesedocuments, by clicking their way through each member of a long staticlist.

Accordingly, what is needed is a system and method for presenting aplurality of documents to a user in a more expeditious fashion than whenutilizing conventional techniques. In a preferred embodiment, the systemand method should be able to analyze documents with multiple topics. Theanalysis would typically be used to produce summary-like abstractions ofthe documents at varying levels of granularity and detail. The systemand method should be easy to implement and cost-effective. Furthermore,the document presentation should contain relevant information fromthroughout the document, not just a selection of sentences that may misssignificant topics. The system and method should allow the presentationto be sensitive to multilayer analysis, should be able to presentsalient and contextualized highlights of a document and should make thedocument available to the user seamlessly, by an active user interface.Finally, the presentation should be adaptable such that a user decideswhether he/she desires to be actively involved in the presentation. Thepresent invention addresses these needs.

SUMMARY OF THE INVENTION

A method and system for the dynamic presentation of the contents of aplurality of documents on a display is disclosed. The method and systemcomprises receiving a plurality of documents and providing a pluralityof topically rich capsule overviews corresponding to the plurality ofdocuments. The method and system also includes dynamically deliveringdocument content encapsulated in the plurality of capsule overviews.

In so doing, a system and method in accordance with the presentinvention can present thematic capsule overviews of the documents tousers. A capsule overiew is derived for the entire document, which willdepict the core content of an average length article in a more accurateand representative manner than utilizing conventional techniques. Thecapsule overviews, delivered in a variety of dynamic presentation modes,allow the user to quickly get a sense of what a document is about, anddecide whether they want to read it in more detail. If so, the systemand method greatly facilitate the process of focused navigation into theparts of the document which may be of particular interest to the user.

In a preferred embodiment, the capsule overviews include a containmenthierarchy which relates the different information levels in a documenttogether, and which includes a collection of highly salient topic stampsembedded in layers of progressively richer and more informativecontextualized text fragments.

The novel presentation metaphors which the invention utilizes are basedon notions of temporal typography, in particular for exploiting theinteractions between form and content.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram illustrating a conventional computer systemthat serves as one type of operating environment for the presentinvention.

FIG. 2 is a simple flow chart illustrating a method for the dynamicpresentation of a plurality of documents in accordance with the presentinvention.

FIG. 3 is a flow chart of a system and method for characterizing thecontent of a document in accordance with the present invention.

FIG. 4 is an example of an article and its segmentation into topicallyseparate sections.

FIG. 5 is a depiction of a TopicsTicker in accordance with the presentinvention.

FIG. 6 is a flow chart of the basic operation of a RSVP viewer inaccordance with the present invention.

FIGS. 7A-7F are depictions of a RAPID SERIAL VISUALIZATION PRESENTATION(RSVP) viewer in accordance with the present invention.

FIGS. 8A-8C are depictions of a ViewTool Viewer in accordance with thepresent invention.

DESCRIPTION OF THE INVENTION

The present invention relates to the rapid presentation of the contentof an average length document. The following description is presented toenable one of ordinary skill in the art to make and use the inventionand is provided in the context of a patent application and itsrequirements. Various modifications to the preferred embodiment will bereadily apparent to those skilled in the art and the generic principlesherein may be applied to other embodiments. Thus, the present inventionis not intended to be limited to the embodiment shown but is to beaccorded the widest scope consistent with the principles and featuresdescribed herein. A system and method in accordance with the presentinvention would typically be utilized in a conventional computer system.

TABLE OF CONTENTS

1. Overview

2. Dynamic Presentation of Document Content

2A. Capsule Overviews

2B. Salience-Based Content Characterization

2C. Anaphora Resolution and Local Salience

2D. Discourse Salience and Capsule Overview

3. Capsule Overviews as Document Abstractions

4. Filling in the Gaps: User Involvement

5. Document Characterization by Topics

5A. Capsule Overview Example

6. Temporal Typography for Dynamic Document Delivery

7. Visualization of Document Content

8. Dynamic Document Viewers

8A. TopicsTicker Viewer

8B. Rapid Serial Visual Presentation (RSVP) Viewer

8C. ViewTool Viewer

8D. Viewer Summary

1. Overview

A system and method in accordance with the present invention wouldtypically be utilized in a conventional computer system.

FIG. 1 is a block diagram illustrating a conventional computer system100, which serves as one type of operating environment for the presentinvention. The computer system 100 includes a display 110, a keyboard120, a pointing device 130, a storage medium 140, a processor 150, and amemory 160, which are all connected by a bus 170. The processor 150operates in conjunction with the memory 160, which are all connected bya bus 170. The processor 150 operates in conjunction with the memory 160to execute a rendering system 180 that enables the processor 150 toprovide, and present, the content characterization from text filesstored in some form of computer-readable medium, such as a CD-ROM, orfrom a network. One of ordinary skill in the art should also recognizethat the present invention could be utilized in a variety of dataprocessing systems, and in particular, display devices, and its usewould be within the spirit and scope of the present invention. Forexample, the present invention could be utilized in Network Computers(NC) and their use would be within the spirit of the present invention.In another example, the present invention could be implemented by aserver utilizing a technique in accordance with the invention to providecontent characterization and a client could provide the resultantdisplay.

The present invention provides a method and system for utilizing novelpresentation metaphors of documents that enables users to rapidly skimthe documents in order to get the “gist” of their contents. This isaccomplished through the dynamic presentation of topically-rich “capsuleoverviews” of documents. The concept of capsule overviews is describedfully in U.S. application Ser. No. 08/974,079, is now U.S. Pat. No.6,185,592 entitled, “A System and Method for Characterizing Content ofText Documents” filed on Nov. 18, 1997, and assigned to the assignee ofthe present application which is incorporated by reference in itsentirety herein.

By utilizing the capsule overviews of documents derived by a system andmethod in accordance with the teachings of the above identifiedapplication, a system and method in accordance with the presentinvention can offer an entirely novel approach to the informationoverload problem. Using topically-rich capsule overviews, a system andmethod in accordance with the present invention can present thematicoutlines of the documents to users. These overviews allow the user toquickly get a sense of what a document is about, decide whether theywant to read it in more detail, and quickly navigate to the point(s) ofdocument of particular interest to them. The following discussion willdescribe with particularity the dynamic presentation of document contentfor average length documents.

2. Dynamic Presentation of Document Content

FIG. 2 is a simple flow chart illustrating a method for the dynamicpresentation of a plurality of documents in accordance with the presentinvention. As is seen, first a plurality of documents are received by adata processing system or the like, via step 202. Next, a plurality oftopically rich capsules overviews which corresponds to the plurality ofdocuments, via step 204. Finally a plurality of documents are presented,via step 206. As before mentioned, by utilizing the above-describedcapsule overviews of documents, a system and method in accordance withthe present invention can offer an effective solution to the informationoverload problem.

The solution in accordance with the present invention to the problem ofeffectively communicating to the end user the ‘gist’ of an on-linedocument, or of a collection of on-line documents, is based on the ideaof relating form and content, by means of dynamic visual treatment ofwritten language, or temporal typography. Only recently has thepossibility of escaping the static and rigid constraints of writing onpaper been fully appreciated. Wong, in Temporal Typography,Characterization of Time-Varying Typographic Forms (Master's thesis, MITMedia Lab, 1995), has stated: “Imagine looking at a small area on acomputer screen. Words appear and disappear on the screen one by one. Asthey appear, meaning is expressed as forms change dynamically over time.The combined effect of the message, form and rhythm express a tone ofvoice, emotion or personality as if you hear a person speak. Althoughthe two mediums, spoken and written words, are vastly different, theanalogy may give you a sense of the expressive potential of temporaltypography.”

The notion, essentially, is to relate highlights of the core meaning ofa message to ways of visually enhancing their impact, or at leastmimicking (some of) their semantic load. In the immediate context ofthis disclosure, this translates to questions of what might beappropriate visual metaphors for representing semantic objects liketopical phrases, shifts in discourse structure, or contextualization ofinformation-bearing phrasal units.

There are several appealing aspects to dynamically presentingabstractions of document content. The user need not be activelyinvolved: as documents arrive at the desktop, they can be analyzed andthe resulting content abstractions can be displayed autonomously. Shouldthe user have the time or inclination to focus on a particular document,interactive controls will be at their disposal; alternatively, each newarrival can be presented under its own schedule, followed by another,and so on. The presentation cycle can be customized to make use ofarbitrary combinations of granularity of expressiveness. Notions likesemantic highlights and demarcation of context are easily mapped ontovisual metaphors, and thus naturally support the expression of contentby means of variations of form. Cognitively, short phrases with highsemantic load are amenable to punctuated display following a naturalrhythm of visual perception.

In summary, delivering document content abstractions dynamically makesit possible to fully exploit a variable depth analysis of documents(which will be discussed in detail below), maintains synchronicity withthe continuous flow of information into one's personal workspace, andallows for smooth integration of passive absorption of the analyses bythe end-user with active participation in more focused document perusal.

The following discussion in accordance with the present inventionhighlights a document analysis technology which seeks to derive documentcontent characterizations designed to exhibit the semantic propertiesdescribed above:

collections of highly salient topical phrases,

embedded in layers of progressively richer and more informativecontextualized text fragments,

with contexts calculated as meaningful fragments defined by acontainment hierarchy of information-bearing phrasal units, and

organized as capsule overviews which track the occurrence of topicalphrases and other discourse referents across the document discourse.

Next, some essential features of temporal typography are described, asit relates to dynamic delivery of document content. These lead into someconclusions about interfaces for content visualization and, accordingly,a range of viewers designed for the purposes of rapid skimming ofon-line documents in order to get the ‘gist’ of their contents ispresented. First, however, the concept of topically-rich capsuleoverviews is discussed in some detail.

2A. Capsule Overviews

A capsule overview is not a true summary, in that it does not attempt toconvey document content as a sequence of sentences. Instead, it is asemi-formal and normalized representation of the document, derived aftera process of data reduction over the original text.

Through capsule overviews, a document's content is characterized in away that is representative of the full flow of the document. This is incontrast to passage extraction techniques, which typically highlightonly certain fragments. Also, capsule overviews are derived by carryingout linguistically intensive analysis of the text in a document, whichseeks semantic prominence of linguistics expressions, rather than justoccurrence of certain pre-specified, or highly frequent, words andphrases—thus the system and method described here can be applied to anydocument, independent of domain, style or genre.

A capsule overview is not an instantiated template. A primaryconsideration of the content characterization system and methoddescribed here is that they should not be specific to any documentsource or type. A capsule overview is a coherently presented list oflinguistic expressions which refer to the most prominent objectsmentioned in the document, i.e., its topic stamps, and furthermoreprovide richer specification of the relational contexts (e.g., verbphrases, minimal clauses) in which these expressions appear.

To further illustrate the concepts associated with a capsule overview,refer now to the following news article shown in Table 1. (Markingcertain phrase units within single quotes is an annotation device, forsubsequent references to the text from within this disclosure document;these annotations were not part of the original article.)

TABLE 1 Priest is Charged with Pope Attack ‘A Spanish Priest’ wascharged here today with attempting to murder the Pope. ‘Juan FernandezKrohn’, aged 32, was arrested after ‘a man armed with a bayonet’approached the Pope while he was saying prayers at Fatima on Wednesdaynight. According to the police, ‘Fernandez’ told the investigators todaythat ‘he’ trained for the past six months for the assault. ‘He’ wasalleged to have claimed the Pope “looked furious” on hearing ‘thepriest's’ criticism of his handling of the church's affairs. If foundguilty, ‘the Spaniard’ faces a prison sentence of 15-20 years.

There are a number of reasons why the title, “Priest Is Charged withPope Attack”, is a highly representative abstraction of the content ofthe passage. It encapsulates the essence of what the story is about:there are two actors, identified by their most prominentcharacteristics; one of them has been attacked by the other; theperpetrator has been charged; there is an implication of malice to theact. The title brings the complete set of salient facts together, in athoughtfully composed statement, designed to be brief yet informative.Whether a present day natural language analysis program canderive—without being primed of a domain and genre—the informationrequired to generate such a summary is arguable. (This is assuming, ofcourse, that natural language generation techniques could, in their ownright, do,the planning and delivery of such a concise andinformation-packed message.) However, part of the task of deliveringaccurate content characterization is being able to identify thecomponents of this abstraction (e.g., ‘priest’, ‘pope attack’, ‘chargedwith’). It is from these components that, eventually, a true summary ofthis document would begin to be constructed.

It is also precisely these components, viewed as phrasal units withcertain discourse properties, that a capsule overview should present asa characterization of the context of the document. Accordingly, in thepresent invention, the most salient and therefore most representativephrasal units, as well as the relational expressions they are associatedwith, are identified to provide the core content of the document.

To describe the generation of capsule overviews in accordance with thepresent invention in more detail refer now to FIG. 3 and theaccompanying text. FIG. 3 is a flow chart of a system and method forcharacterizing the content of a document in accordance with the presentinvention. As is seen in the figure, first a list of discourse referentsare provided within the document via step 302. Then, the document isdivided into separate segments based upon changes in topic, via step304. Thereafter, the discourse referents are linked together intoco-reference classes, via step 306. Next, the salience for each of thediscourse referents is calculated, via step 308. After thosecalculations are performed, then it is determined which discoursereferents have the highest values within a segment, via step 310.

The core information unit that the invention concerns itself with is theset of discourse referents in a document. Discourse referents aretypically realized as noun phrases. In essence, these are theentities—actors and objects—around which a story unfolds. In order todetermine, and maintain, an accurate model of what a document is about,it is necessary to be able to identify the ways in which the same entityis referred to in the text, as well as to establish co-referentialityamong different ‘mentions’ in the text of the same entity. The sampledocument in Table 1 provides examples of the same entity being referredto in different ways in the text (“priest”, “a Spanish Priest”,“Fernandez”, and “he”, in the second paragraph, all refer to the sameperson), as well as of different entities being referred to by the sametext string (“he” in the first paragraph refers to the Pope, while “he”in the second paragraph refers to the priest).

Thereafter, discourse referents with the highest salience values arelabeled as topic stamps, via step 312. The local contexts around each ofthe topic stamps are identified, via step 314. Finally, from thisinformation a capsule overview of the document is constructed with agiven degree of granularity via step 316. A key concept associated withgeneration of the capsule overviews is the calculation of saliencevalues for the discourse referents, which are then used for determiningtopic stamps in the document. The following will discuss salience basedcalculations in more detail.

2B. Salience-Based Content Characterization

Salience is a measure of the relative prominence of objects indiscourse: objects with high salience are the focus of attention; thosewith low salience are at the periphery. In an effort to resolve theproblems facing a term-based approach to content characterization, asdiscussed in the background of the application, a procedure inaccordance with the present invention has been developed which uses asalience feature as the basis for a “ranking by importance” of anunstructured referent set; ultimately, this facilitates topic stampidentification. By determining the salience of the members of a referentset, an ordering can be imposed which, in connection with an appropriatechoice of threshold value, permits the reduction of the entire referentset to only those expressions that identify the most prominentparticipants in the discourse. This reduced set of terms, in combinationwith information about local context at various levels of granularity(verb phrase, minimal clause, sentence, etc.) offers an accurate anddetailed characterization of a document's content. This may then befolded into an appropriate presentation metaphor such as that will bedescribed hereinafter. Crucially, such an analysis satisfies someimportant requirements of usability of document content abstractions: itis concise, it is coherent, and it does not introduce cognitiveoverload. In a more general sense, this method utilizes a strategy forscaling up the phrasal analysis techniques utilized by standard termidentification and template instantiation technologies, which has at itscore the utilization of a crucial feature of discourse structure: theprominence, over some segment of text, of particular referents—somethingthat is missing from the traditional technology for ‘bare’ terminologyidentification.

2C. Anaphora Resolution and Local Salience

For the purposes of determining how discourse referents relate toobjects in the world of the document, a simplifying assumption is madethat every noun phrase identified by extended phrasal analysisconstitutes a “mention” of a participant in the discourse. In order todetermine which expressions constitute mentions of the same referent,the method described here crucially relies upon being able to carry outanaphora resolution and co-referent identification. Linguisticexpressions that are identified as coreferential are grouped intoequivalence classes, and each equivalence class is taken to represent aunique referent in the discourse. The set of such equivalence classesconstitutes the full referent set from which, ultimately, topic stampswill be derived.

A distinctive feature of the anaphora resolution algorithm is that ithas been specially adapted to work from a shallow syntactic base:specifically, it does not require full syntactic analysis of the text.This makes the method applicable to any text document, irrespective ofits domain, style, or genre. This type of anaphora resolution algorithmis described, in full detail, in the paper “Anaphora for Everyone:Pronominal Anaphora Resolution Without a Parser,” by C. Kennedy and B.Boguraev, which was presented at the 16th International Conference onComputational Linguistics, Copenhagen, Denmark, Aug. 5-9, 1996.

The immediate result of anaphora resolution is to reduce the extendedphrase set of all mentions of objects in the discourse; the largerconsequence is that it provides the basis for the identification oftopic stamps, as it introduces both a working definition of salience anda formal mechanism for determining the salience of particular linguisticexpressions. This connection between anaphora resolution, co-referenceidentification, discourse salience, and semantic prominence is describedin fuller detail in “Anaphora for Everyone: Pronominal AnaphoraResolution Without a Parser,” (C. Kennedy and B. Boguraev, inProceedings of COLING-96 (16th International Conference on ComputationalLinguistics), Copenhagen, DK, Aug. 5-9, 1996) and “Anaphora in a WiderContext: Tracking Discourse Referents” (C. Kennedy and B. Boguraev, inW. Wahlster, Editor, Proceedings of ECAI-96 (12th European Conference onArtificial Intelligence), Budapest, Hungary, Aug. 11-16, 1996. JohnWiley and Sons, Ltd., London/New York).

Roughly speaking, the anaphora resolution procedure locates anantecedent for an anaphoric expression by first eliminating allimpossible candidate antecedents, then ranking the remaining candidatesaccording to a salience measure and selecting the most salient candidateas the antecedent. This measure, which is referred to as ‘localsalience’, is a function of how a candidate antecedent expressionsatisfies a set of grammatical, syntactic, and contextual parameters.These constraints are typically referred to as “salience factors”.Individual salience factors are associated with numerical values, asshown below.

TABLE 2 “sent”: 100 iff the expression is in the current sentence.“cntx”: 50 iff the expression is in the current discourse segment.“subj”: 80 iff the expression is a subject “exst”: 70 iff the expressionis in an existential construction. “poss”: 65 iff the expression is apossessive. “acc”: 50 iff the expression is a direct object. “dat”: 40iff the expression is an indirect object. “oblq”: 30 iff the expressionis the complement of a preposition. “head”: 80 iff the expression is notcontained in another phrase. “arg”: 50 iff the expression is notcontained in an adjunct.

The local salience of a candidate is the sum of the values of thesalience factors that are satisfied by some member of the equivalenceclass to which the candidate belongs; values may be satisfied at mostonce by each member of the class. The most important aspect of thesenumerical values for our concerns is that they impose a relationalstructure on the salience factors, which in turn provides the basis forordering referents according to their relative prominence in thediscourse (in other words, what is important is not so much the valuesthemselves but the fact that they denote that, for instance, “subj”factor indicates higher prominence than “ac”, itself more prominent than“oblq”, and so forth).

2D. Discourse Salience and Capsule Overviews

An important feature of local salience is that it is variable: thesalience of a referent decreases and increases according to thefrequency with which it is mentioned (taking into account subsequentanaphoric expressions). When an anaphoric link is established, theanaphor is added to the equivalence class to which its antecedentbelongs, and the salience of the class is boosted accordingly. If areferent ceases to be mentioned in the text, however, its local salienceis incrementally decreased; this reflects decay in its prominence. Thisapproach works well for the purpose of anaphora resolution, because itprovides a realistic representation of the antecedent space for ananaphor by ensuring that only those referents that have mentions withina local domain have increased prominence. However, the ultimate goal ofsalience-based content characterization differs from that of anaphoraresolution in an important respect. In order to determine whichlinguistic expressions should be presented as broadly representative ofthe content of a document, it is necessary to generate a picture of theprominence of referents across the entire discourse, not just within alocal domain.

For illustration of the intuition underlying this idea, consider thenews article discussed in Table 1. Intuitively, the reason why “priest”is at the focus of the title is that there are no less than eightreferences to the same actor in the body of the story (marked by singlequotes in the example); moreover, these references occur in prominentsyntactic positions: five are subjects of main clauses, two are subjectsof embedded clauses, and one is a possessive. (This example alsoillustrates the rationale behind the above-described salience factors.)Similarly, the reason why “Pope attack” is the secondary object of thetitle is that a constituent of the compound, “pope”, also receivesmultiple mentions (five), although these references tend to occur inless prominent positions (two are direct objects).

In order to generate the broader picture of discourse structure neededto inform the selection of certain expressions as most salient, andtherefore most representative of content, an elaboration is introducedof the local salience computation described above that uses the sameconditions to calculate a non-decreasing, global salience value forevery referent in the text. This non-decreasing salience measure, whichis referred to as ‘discourse salience’, reflects the distributionalproperties of a referent as the text story unfolds. In conjunction withthe “tracking” of referents made available by anaphora resolution—asdiscussed at some length in “Anaphora in a wider context: Trackingdiscourse referents” (C. Kennedy and B. Boguraev, in W. Wahlster,editor, Proceedings of ECAI-96 (12th European Conference on ArtificialIntelligence), Budapest, Hungary, Aug. 11-16, 1996. John Wiley and Sons,Ltd, London/New York)—discourse salience provides the basis for acoherent representation of discourse structure that indicates thetopical prominence of individual mentions of referents in isolatedsegments of text.

Most importantly, discourse salience provides exactly the informationthat is needed to impose the type of importance-based ranking ofreferents which is required for the identification of topic stamps.Specifically, by associating every referent with a discourse saliencevalue, the topic stamps can be identified for a segment of text S as then highest ranked referents in S, where n is a scalable value.

The notion “segment of text” plays an extremely important role in thecontent characterization task, as it provides the basicinformation-structuring units around which a capsule overview for adocument is constructed. Again, the example from Table 1 gives a usefulillustration of the important issues. The reason that the title of thispassage works as an overview of its content is because the text itselfis fairly short. As a text increases in length, the “completeness” of ashort description as a characterization of content deteriorates. If theintention is to use concise descriptions consisting of one or twosalient phrases—i.e., topic stamps—along with information about thelocal context in which they appear as the primary information-bearingunits for a capsule overview, then it follows that texts longer than afew paragraphs must be broken down into smaller units or “segments”.

In order to solve this problem, a document is recast as a set of“discourse segments”, which correspond to topically coherent, contiguoussections of text. One approach to segmentation which works well for thepurposes of this method implements a similarity-based algorithm alongthe lines of that described by Hearst, in her paper entitled“Multi-Paragraph Segmentation of Expository Text.” (M. Hearst, in 32ndAnnual Meeting of the Association for Computational Linguistics, LasCruces, N.M., 1994), which identifies discourse segments in text using alexical similarity measure. By calculating the discourse salience ofreferents with respect to the results of discourse segmentation, eachsegment can be associated with a listing of those expressions that aremost salient within the segment, i.e., each segment can be assigned aset of topic stamps. The result of these calculations, namely the set ofsegment-topic stamp pairs, ordered according to linear sequencing of thesegments in the text, can then be returned as the capsule overview forthe entire document. In this way, the problem of contentcharacterization of a large text is reduced to the problem of findingtopic stamps for each discourse segment.

3. Capsule Overviews as Document Abstractions

Striving to balance the conflicting requirements of depth and accuracyof a summary with those of domain- and genre-independence, the notion ofa capsule overviews has been developed as content abstraction for textdocuments, explicitly designed to capture “aboutness”. One of theproblems of information management, when presented with a growingsurplus of text documents, is getting some appreciation—rapidly,compactly, and yet with a usable degree of depth andrepresentativeness—of the information contained in a document.Informally, this is usually referred to as the “aboutness” of adocument, and is represented as a set of highly salient, and by thattoken most representative, phrases in the document. By viewingtopicality in its stricter, linguistic, sense, the previous sectiondefined topic stamps to be the most prominent of these phrases,introduced into, and then elaborated upon, the document body. On thebasis of this definition, the above-identified computational,algorithmic, procedure has been developed for generating a set ofabstractions for the core meaning in the document, ultimately resultingin a capsule overview of the document based upon suitable presentationof the most representative, and most contentful, expressions in thetext. These abstractions comprise layered and inter-related phrasalunits at different levels of granularity and depth of document analysis.To further describe this concept of granularity refer now to thefollowing discussion.

Granularity is closely tied to context. In general, the information in agiven sentence is best expanded by being able to position this sentencein its paragraph context; likewise, the theme and topic(s) in aparagraph can be further elaborated by relating the paragraph to thesegment of discourse which encompasses the theme in its entirety. Thisis a natural containment hierarchy, relating the different informationlevels in a document together. Such a hierarchy can also be extended insub-sentential direction: phrasal units indicative of topicality areclearly wholly contained in sentences; furthermore, a phrasalcontainment hierarchy could also be utilized to provide contextualizedinformation concerning the topical phrases themselves.

Imagine that in the second example above (Example 2, page 5) somemechanism has determined that the phrase “Scheduled IRS Layoffs” istopically indicative. Assuming some focused mining in the vicinity ofsuch an ‘anchor’ by a phrasal grammar of a certain type, this topicphrase could be further contextualized to “Scheduled IRS Layoffs For 500Are Canceled”. This is an example of phrasal containment ofinformation-bearing phrasal units. Similar expansion of topic in contextmight yield, for the initial discourse segment of the document,progressively larger and more informative fragments from it:

EXAMPLE 4

TOPICAL PHRASE: “Scheduled IRS Layoffs” TOPIC IN RELATIONAL CONTEXT:“there will be no layoffs” TOPICAL SENTENCE: “Yesterday, the IRS saidthere will be no layoffs” SENTENCE IN PARAGRAPH CONTEXT: “More than ayear ago, The Internal Revenue Service planned widespread job cuts.Yesterday, the IRS said there will be no layoffs.” PARAGRAPH WITHINTOPICALLY COHERENT DISCOURSE THEME: “More than a year ago, the InternalRevenue Service planned widespread job cuts. Yesterday, the IRS saidthere will be no layofs.” Confronted with congressional criticism andcalls for reform in light of some highly pubilcized reports of abusiveactions toward taxpayers, as well as staunch union opposition to thecuts, the IRS said employees at risk of losing their jobs would bereassigned to improve ‘customer service,’ help taxpayers resolveproblems and increase compliance with tax laws.”

This example illustrates the notion of granularity of document analysis,and is especially indicative of how a containment hierarchy of layeredinformation—from very compact and representative topical phrases all theway to full and rich discourse segments—can be utilized to represent andmaintain strong notion of contextualization in a document abstraction.

The example also shows the value of being able to identify phrasal unitssmaller than sentences, arrange them in layers corresponding to theinformational containment hierarchy, and perform certain semanticoperations over them. These operations fall largely in the area ofreference identification, co-referentiality, and topic tracking;consider, for example, the processes of relating “layoffs” to “scheduledIRS layoffs”, identifying “Internal Revenue Service” and “IRS” asreferring to the same object, resolving anaphora in general and soforth.

4. Filling in the Gaps: User Involvement

It is clear that granularity of analysis and containment hierarchy ofinformation-bearing phrasal units with different (yet complementary)discourse properties and function could be utilized very effectively toimplement a “zooming” function into and/or out of a given document. Inthis way finding out more of what is behind a document “summary” is, ineffect, filling in the gaps in such a summary in a controlled fashion,guided by incrementally revealing progressively larger and moreinformative contexts.

Conceptually, this is not dissimilar to the notion of “percentage ofshrink factor”, typically utilized by sentence-based summarizes, where auser can specify that a document should be condensed to N percent of itsfull extent. There is, however, a crucial difference here. Whenre-casting a document from, say, 10% to 20% shrink factor, there is noway to specify ahead of time, nor to know after the event, how theadditional sentences relate to the original 10%. In contrast, when adocument is re-cast in terms of information-bearing units a level higherthan what its current representation uses—for instance, as a set ofrelational contexts immediately surrounding its topic stamps—there is aguarantee that the user's sense of what the document is about isincrementally and monotonically enriched.

This makes it possible to use the capsule overview technology inaccordance with the present invention to enable a user to get animmediate and accurate impression of what a particular document isabout. As a capsule overview is a small window into the core content ofa document, it is a useful abstraction for compact representation ofcontent. Once engaged, however, the user can still use this window to‘drill’, arbitrarily deeply, into the underlying information layers.Before discussing the approach to visualization of document content andpresentation metaphors for using capsule overviews as mediators, andfacilitators, of dynamic document content delivery, the basic notions oftopically rich capsule overviews as layered abstractions of documentcontent are exemplified hereinbelow.

5. Document Characterization by Topics

5A Capsule Overview Example

The following discussion describes an example of an article the analysisof which utilizes the present invention. As described in sections 2 and3 above, the operational components of salience-based contentcharacterization fall in the following categories: discoursesegmentation; phrasal analysis (of nominal expressions and theirrelational contexts); anaphora resolution and generation of a referentset; calculation of discourse salience and identification of topicstamps; and enriching topic stamps with information about relationalcontext(s). Some of the functionality follows directly from technologydeveloped for the purposes of phrasal identification, suitably augmentedwith mechanisms for maintaining phrase containment; in particular, bothrelation identification and extended phrasal analysis are carried out byrunning a phrasal grammar over a stream of text tokens tagged forlexical, morphological, and syntactic information, and for grammaticalfunction; this is in addition to a grammar mining for terms and,generally, referents.

In a preferred embodiment the base level linguistic analysis is providedby the LINGSOFT supertagger; see F. Karlsson, A. Voutilainen, J.Heikkila, and A. Antilla, “Constraint Grammar: A Language-IndependentSystem for Parsing Free Text”, Mouton de Gruyter, 1995. The later, moresemantically-intensive algorithms are described in detail in “Anaphorafor Everyone: Pronominal Anaphora Resolution Without a Parser” (C.Kennedy and B. Boguraev, in Proceedings of COLING-96 (16th InternationalConference on Computational Linguistics), Copenhagen, DK, 1996) and“Anaphora in a Wider Context: Tracking Discourse Referents” (C. Kennedyand B. Boguraev, in W. Wahlster, editor, Proceedings of ECAI-96 (12thEuropean Conference on Artificial Intelligence), Budapest, Hungary,1996. John Wiley and Sons, Ltd, London/New York). The procedure isillustrated by highlighting certain aspects of a capsule overview of anarticle 400 shown in FIG. 4. The document is of medium-to-large size(approximately four pages in print), and focuses on the strategy ofGilbert Amelio (former CEO of Apple Computer) concerning a new operatingsystem for the Macintosh. Too long to quote here in full, the followingpassage from the beginning of the article contains the first, second andthird segments (shown at 402, 404, and 406 in FIG. 4), as identified bythe discourse segmentation component. (In the figure, segment boundariesare marked by extra vertical space; this markup is for illustrationpurposes only, and indicates the result of running the discoursesegmentation algorithm. No such demarcation exists in the source of thearticle itself).

The capsule overview was automatically generated by a fully implemented,and operational, system, which incorporates all of the processingcomponents identified above. The relevant sections of the overview ofthe article 400 (for the three segments of the passage quoted) are shownin Tables 3, 4 and 5 below.

The topic stamps for the three segments 402, 404, and 406 constitute thecore data out of which a capsule overview is constructed; these areshown underlined immediately following the segment sequence identifiers(in square brackets). The capsule overview itself displays the topicstamps (highlighted in single quotes) in their relational contents.

TABLE 3 [1] Apple; Microsoft ‘Apple’ would swoop in and take‘Microsoft's’ customers? ‘Apple’ lost $816 million; ‘Microsoft’ made$2.2 billion. ‘Microsoft’ has a market value thirty times that of‘Apple’ it makes sense for ‘Apple’ ‘Apple’ is in a position ‘Apple’needs something dramatic

TABLE 4 [2] desktop machines; operating system Today's ’desktopmachines’, he [Gilbert Amelio] says Tomorrow's ‘machines’ mustaccommodate rivers of data Time to scrap your ‘operating system’ andstart over The ‘operating system’ is the software that controls to gowith the ‘reengineered operating system’

TABLE 5 [3] Gilbert Amelio; new operating system ‘Amelio’, 53, brings alot of credibility to this task ‘His’ [Gilbert Amelio] resume includeswhere is ‘Amelio’ going to get this ‘new operating system’? radicalredesign in ‘operating systems’ that ‘Amelio’ is talking about

The division of this passage into segments, and the segment-basedassignment of topic stamps, exemplifies a capsule overview's “tracking”of the underlying coherence of a story. The discourse segmentationcomponent recognizes shifts in topic—in this example, the shift fromdiscussing the relation between Apple and Microsoft to some remarks onthe future of desktop computing to a summary of Amelio's background andplans for Apple's operating system. Layered on top of segmentation arethe topic stamps themselves, in their relational contexts, at a phrasallevel of granularity.

The first segment (Table 3) sets up the discussion by positioning Appleopposite Microsoft in the marketplace and focusing on their majorproducts, the operating systems. The topic stamps identified for thissegment, “apple” and “microsoft”, together with their local contexts,are both indicative of the introductory character of the openingparagraphs and highly representative of the gist of the first segment.Note that the apparent uninformativeness of some relational contexts,for example, “. . . ‘Apple’ is in a position . . . ”, does not pose aserious problem. An adjustment of the granularity—at capsule overviewpresentation time (see below)—reveals the larger context in which thetopic stamp occurs (e.g., a sentence), which in turn inherits the hightopicality ranking of its anchor: “Apple' is in a position wherestanding pat almost certainly means slow death.”

For the second segment (Table 4) of the sample, “operating system” and“desk-top machines” have been identified as representative. The set oftopic stamps and contexts illustrated provides an encapsulated snapshotof the segment, which introduces Amelio's views on coming challenges fordesktop machines and the general concept of an operating system. Again,even if some of these are somewhat under-specified, more detail iseasily available by a change in granularity, which reveals thedefinitional nature of the even larger context “The ‘operating system’is the software that controls how your computer's parts . . . ”

The third segment (Table 5) of the passage exemplified above isassociated with the stamps “Gilbert Amelio” and “new operating system”.The reasons, and linguistic rationale, for the selection of theseparticular noun phrases as topical are essentially identical to theintuition behind “priest” and “Pope attack” being the central topics ofthe example in Table 1. The computational justification for the choiceslies in the extremely high values of salience, resulting from takinginto account a number of factors: co-referentiality between “amelio” and“Gilbert Amelio”, co-referentiality between “amelio” and “his”,syntactic prominence of “amelio” (as a subject) promoting topical statushigher than for instance “Apple” (which appears in adjunct positions),high overall frequency (four, counting the anaphor, as opposed to threefor “Apple”—even if the two get the same number of text occurrences inthe segment), and boost in global salience measures, due to “priming”effects of both referents for “Gilbert Amelio” and “operating system” inthe prior discourse of the two preceding segments. Compared to a singlephrase summary in the form of, say, “Amelio seeks a new operatingsystem”, the overview for the closing segment comes close; arguably, itis even better than any single phrase summary.

As the discussion of this example illustrates, a capsule overview isderived by a process which facilitates partial understanding of the textby the user. The final set of topic stamps is designed to berepresentative of the core of the document content. It is compact, as itis a significantly cut-down version of the full list of identifiedterms. It is highly informative, as the terms included in it are themost prominent ones in the document. It is representative of the wholedocument, as a separate topic tracking module effectively maintains arecord of where and how referents occur in the entire span of the text.As the topics are, by definition, the primary content-bearing entitiesin a document, they offer accurate approximation of what that documentis about.

6. Temporal Typography for Dynamic Document Delivery

Dynamic content delivery is based on ideas of temporal typographydeveloped by Wong (Y. Y. Wong, Temporal typography, characterization oftime-varying typographic forms, Master's thesis, MIT Media Lab, 1995).This work develops a synergy of psychological studies of reading,graphic design, and temporal presentation of text. Graphic designhistory is rich with examples of experimenting with visual treatment ofwritten language. Designers have begun to explore temporal presentationof text in television and film media. Studies of reading, which to alarge extent form the basis of Wong's work, have explored dynamicpresentation of content, related to the interactions between meaning andintent of a text-based message. However, Wong's studies of the dynamicrelationship between meaning and delivery formats assume that theannotations for meaning in her experiments have been done by hand. Incontrast, this invention is concerned with leveraging an automaticdocument content analysis technology, capable of delivering meaninganalyses and content abstractions precisely of the kind which can beeffectively coupled with dynamic content delivery.

7. Visualization of Document Content

Previously, the predominant current mechanism for mediating the spectrumbetween a summary of a document and a complete version of the samedocument was briefly discussed. In addition to a direct hypertextrendering of extracted sentences, in their full document s contexts, twovariations on this approach are the VESPA slider and HYPERGEN. VESPA isan experimental interface to Apple's sentence-based summarizer (AdvancedTechnologies Group, Apple Computer, Cupertino, Calif., Apple InformationAccess Toolkit: Developer Notes and APIs, 1997), whose main feature is aslider which dynamically readjusts the shrink factor of a documentsummary. HYPERGEN exploits notions of phrasal containment withinsentence units, in an attempt to elaborate a notion similar to that ofgranularity of analysis and context introduced earlier in this document:in a process called sentence simplification, Mahesh (K. Mahesh,Hypertext summary extraction for fast document browsing, in Proceedingsof AAAI Spring Symposium on Natural Language Processing for the WorldWide Web, ages 95-104, Stanford, Calif., 19975) uses phrases as“sentence surrogates”, which are then straightforwardly rendered ashypertext links to the sentences themselves.

As part of an ongoing investigation of visualizing large informationspaces, researchers at Xerox PARC have looked at a variety of structureddata types (such as hierarchically structured data, calendars, andbibliographic databases). Some general principles derived from that workhave been applied to unstructured documents: the DOCUMENT LENS is atechnique for viewing 2-D information, designed for componentpresentations of multi-page documents. Without going into detail, whatis of particular relevance here is the strong notion of focus pluscontext which drives the design. The visualization, however, does littlein terms of using any kind of document summary or other abstraction, andis of a predominantly static nature (even though it is extremelyresponsive to user interaction, as it attempts to combine a ‘bird's eyeview’ of the entire document with a page browsing metaphor). Morerecently experimental prototypes have been developed for interfaceswhich treat term sets (in the information retrieval sense, i.e. flatlists of index terms) as document surrogates: the focus of such designsis visually on presenting notions like distribution of terms across thedocument, and on mediating access to local context for a given term (R.Rao, J. O. Pedersen, M. A. Hearst, J. D. Macinlay, S. K. Card, L.Masinter, P.-K. Halvorsen, and G. G. Robertson, “Rich interaction in thedigital library”, Communication of the ACM, 38(4):29-39, 1995; M. A.Hearst, “Tilebars: Visualization of term distribution information infull text information access,” in ACM SIGCHI Conference on Human Factorsin Computing Systems, Denver, Colo., 1995). Ultimately, however, theseinterfaces still offer only a direct link between two states, thedocument surrogate and its full form.

With the migration of news delivery over the World Wide Web and thegrowth of information ‘push’ vendors, some new methods are beginning toemerge for presentation of news stories which use notions of dynamicdelivery of content. Most of these are variations on the same theme:news delivery using a ticker metaphor. Thus both ABC's news site(http://www.abc.com) and Pointcast (http://www.pointcast.com) employ atraditional horizontal ticker, CNN Interactive (http://www.cnn.com)arrange their ticker vertically, while CBS (http://www.uttm.com) combinea ticker with photos from a major story.

The important insight here is that tickers are dynamic objects, whichcan be programmed to continuously update themselves from a news feed andto cycle in a pre-defined regime, therefore not requiring userintervention. Furthermore, they can be dispatched to an area of theworkspace (monitor screen) where constant, yet inobtrusive, newsdelivery can take place in the periphery of the user's main activity:thus a choice exists between proactive engagement with the news source,and passive (and almost subliminal) monitoring of news data.

None of the examples above, however, combines a ticker with an automaticsummarization engine. To a large extent this is becausesentences—especially inconsecutive ones, in the absence of visualmarkers for discontinuity—do not lend themselves easily into the word byword, left to right, presentation mode. This is clearly a situationwhere phrasal units of a sub-sentence granularity can be utilized muchmore effectively. In addition, psychological experiments on activereading (Y. Y. Wong, Temporal typography, characterization oftime-varying typographic forms, Master's thesis, MIT Media Lab, 1995)show that when text is presented dynamically in the manner of a ticker,subjects' reading speeds are significantly slower than for textpresented statistically. On the other hand, dynamic presentations oftext which show words or short phrases in the same location, butserially, one after the other, have reading speeds comparable to thosefor normal static texts.

To date, no applications have been developed utilizing temporaltypography for dynamic delivery of content abstractions. Wong has lookedat how dynamic type in general can be used for four differentcommunicative goals: expressive messages, dialogue, active reading andreal time conversation Most relevant to this discussion are herexperiments on active reading. In one of these she used a basic RSVP(Rapid Serial Visual Presentation) method (words or phrases presentedsequentially one after another, on the same line and at the sameposition) to deliver a sequence of news headlines. In a second set ofexperiments called HIGHWAY NEWS, three dimensions are utilized, combinedwith a zooming motion, to present a sequence of text highlights. “Newsheadlines are placed one after another in the z-dimension. Headlines arepresented serially according to active input from the reader presses amouse button to fly through the rows of headlines—as if flying overhighway of text.” These experiments show the strong feasibility of highimpact, low engagement, delivery of semantically prominent textfragments being utilized as a powerful technique for visualizing certaintypes of inherently linear information.

None of the work cited above relies on automatically generated meaningabstractions as its input; yet, it is clear that the topically-richcapsule overviews generated by the document analysis technologydiscussed in sections 2 and 3, and exemplified in section 5, are justthe kind of semantic highlights which Wong's experiments in activereading assume. Conversely, up till now there has been no thought as tohow the nature of topic-based capsule overviews in particular would fitthe notion of dynamic type. This is a key feature of the presentinvention, and is discussed below.

8. Dynamic Document Viewer

Below will be described three embodiments of systems or viewers forproviding dynamic presentation of documents. These three embodimentswill be hereinafter referred to as the TopicsTicker Viewer, Rapid SerialVisual Presentation (RSVP) Viewer and the ViewTool Viewer. It should beunderstood that although these three viewers are described, one ofordinary skill in the are recognizes a variety of views could beutilized and they would be within the spirit and scope of the presentinvention. To more particularly describe these embodiments refer now tothe following discussion in conjunction with the accompanying Figures.

The above three embodiments provide different dynamic views of documentcontent. The difference is largely due to the variety of operationalenvironments in which the viewers have been applied. A variation on anews ticker is designed to be deployed in situations where screen realestate may be at premium, or where several different channels ofinformation may be delivered simultaneously to the same ‘in-box’;typically such situations assume that users would only want to get avery general idea of document content. For situations where more screenreal estate might be available, and/or it may be known ahead of timethat more detail concerning document content might be required, adifferent viewer develops ideas from rapid serial visual presentation(RSVP). Yet another interface caters to the need to be able to getimmediate access to the full text of a document, without losing thebenefits of rapid skimming through content highlights while fillymaintaining information about the larger context.

All of the viewers assume an environment where incoming documents getanalyzed to capsule overview level (See FIG. 3); the results of theanalysis are embedded into the original text by means of, for example,special purpose tags.

8A. TopicsTicker Viewer

TopicsTicker Viewer as shown in FIG. 5 is a minimalist, hands-free,peripheral-vision-directed ticker tape, with certain aspects of itsdisplay tuned for serial delivery of a document's topic stamps: thestring in the left panel is the document title, and the right panel iswhere the display cycles, continuously, through the document's topicstamps. When running over a set of documents, switching from onedocument to the next is cued by a color change and a vertical scroll.

8B. Rapid Serial Visual Presentation (RSVP) Viewer

FIG. 6 is a flow chart of the operation of the RSVP viewer. First, alist or plurality of consecutively ordered documents are provided, viastep 602. Next, the first document in order is selected, via step 604.Thereafter, the first topic stamp from the current document is selectedfrom the capsule overview, via step 606: The relational context for thattopic stamp is selected from the capsule overview, via step 608. Thecanonical form for that topic stamp is retrieved, via step 610. Then thetopic stamp is displayed in the background, in translucent type, and itsassociated relational context is displayed in the foreground, in heaviertype, via step 612. Next, a time period for displaying the relationalcontext is calculated, via step 614. This time period is based upon theamount of information displayed. The topic stamp and relational contextare then displayed for that time period, via step 616. It is thendetermined if there are other topic stamps, via step 618. If there areother topic stamps, then the next topic stamp is selected, via step 620and its associated relational context is selected, via step 608, and thecycle is repeated. If on the other hand, there are no other topicstamps, a visual worker is displayed, indicating a document change, viastep 622. It is then determined if there are other documents, via step624. If there are no other documents then recycle back from the firstdocument. If there are other documents, then the next document inconsecutive order is selected, via step 626. Thereafter, its first topicstamp is selected, via step 606, and the cycle is repeated.

This continuous cycle defines the basic mode of operation for RSVPviewer. It can, as will be discussed below, be interrupted by the userat any time.

In its basic mode with no user interaction, the RSVP Viewer cyclesthrough all salient relational contexts in a document, maintaining theorder in which they appear in the text. As shown in FIGS. 7A-7B, eachcontext phrase is displayed as the prominent object on the screen 702;at the same time the context is overlaid onto topic expansions(displayed as translucent text) 704. This facilitates furtherinterpretations of the context strings by the user: expansions relatephrasal contractions in the string displayed to their full canonicalforms in the text, make clear antecedents of dangling anaphors, and soforth. Note, for instance, the background display (FIG. 7C) 704 of thefull form of the antecedent for the anaphoric “he” in the foreground702: in this particular context, “he” has been resolved to “GilbertArmelio”.

Cycling though the complete set of salient contexts, in their originalsequence, offers a good indication of aboutness at a given level ofdepth and detail. Granularity of display is adjustable via a parameter:thus RSVP Viewer could be reduced to a TopicsTicker Viewer by onlycycling through the document's topic stamps, or it could be used todisplay sequences of sentences. Relational contexts offer just the rightbalance between terseness (phrases are more easily perceived andassimilated than sentences) and informativeness (phrases larger than‘bare’ topic stamps convey richer data). The amount of time a phrase isdisplayed is dynamically calculated, based on studies of active readingand perception; the intent is to optimize the full document displayregime so that individually, each phrase can be processed by the user,while globally, the entire set of salient contexts can be cycled throughrapidly.

There are provisions for maintaining overall context, by continuouslydisplaying the title of the current document 706, as well as forallowing context switching, by user selection of a document from apop-up menu 708 (co-located with the title), via for example by a mouseclick.

RSVP Viewer is designed as an entirely autonomous viewer: after all thecontent highlights in a document have been displayed, the next documentwill be loaded and the cycle repeated (just like in TopicsTicker Viewer,a suitable visual cue signals document change). This makes it veryappropriate for situations where readers do not have much time,bandwidth, or opportunity, to interact with the display, but they wouldwant to be peripherally aware of new documents that come into thesystem. On the other hand, if a particular context catches the userattention, a ‘zoom’ mechanism makes use of the multiple levels ofanalysis of the document (as defined via the containment hierarchydiscussed in Section 3, “Capsule Overviews as Document Abstractions”).

This will reveal, on demand, progressively larger and more well detaileddocument fragments: sentences, paragraphs and segments. FIGS. 7B, 7D and7E viewed in this sequence give an indication of how progressivelyinformative contexts are revealed on demand: 7B displays a topic and itscontent, in FIG. 7D the latter is contextualized to the sentencecontaining it and in FIG. 7E, this sentence is displayed in the contentof the relevant (containing) paragraph. Foreground and backgroundinformation are always differentiated by hierarchies of type. Thetransition between displays—e.g., from 7B to 7D, or from 7D to 7E, isaccentuated by a visual “zoom” mechanism. In such a hierarchy, about thelarger context is always easily available: for instance, furtherspecifics concerning what “he says” (see FIG. 7c) is immediatelyavailable by a single click in the display area, the result of which isshown in FIG. 7F.

At any given point of time, and depth of detail, the display uses acombination of visual cues to highlight the information-bearing unitwhich is in focus, and associate this with the larger context in whichit appears in the original source. In particular, properties of type,both static and dynamic, come to convey various aspects of the documentanalysis: primary focus of attention is denoted by using heavy blacktypeface; background context, by using translucent text; semanticrelatedness, by overlaying the focus and context onto the same displayarea; different level of attention to detail by visually andperceptibly, zooming in when more detail is requested, and by zoomingout when the user retreats back into the default “fly-through, frombird's eye view,” mode. Note that while such visual devices are veryeffective for delivering document highlights, they rely crucially onbeing able to carry out the layered analysis described with respect tocapsule overviews.

The RSVP Viewer is particularly well-suited for deployment in a screensaver mode, in a background window on a desktop machine, or on a largescreen projection in communal areas. In any of these situations, a topicor context might catch a reader's peripheral attention, and then theycan decide to take a further look. RSVP Viewer thus naturally extends,and fits into, the emerging ‘push’ model of information delivery.

8C. ViewTool Viewer

Referring now to FIGS. 8A-8C, what is shown is an embodiment of theViewTool viewer. The ViewTool viewer freely borrows some of the ideas ofRSVP viewer. However, the emphasis here is to present a fuller overviewof the salient topic stamps in a document, one place, a single“overview” panel 804. This overview is contextualized to a document‘thumbnail’ 816, indicative of the distribution of these highly salientobjects in the text. At the same time, a separate ‘details’ area 806constantly displays additional information pertinent to the currentinformation-seeking context deployed by the user. The details area 806is used both for dynamic display of richer contexts, as in the RSVPviewer for providing access to the full text, or topically coherentsegments from it, on demand. Thus, the aim of this viewer is to developa more elaborate notion of context, while maintaining permanent focus onthe salient highlights (topic stamps) in the document. The ViewToolviewer further seeks to offer more interactivity to the user, in wayswhich make the targeted exploration of portions of the document naturaland transparent.

The ViewTool viewer places the capsule overview of a document within thecontext of the document itself This is maintained by synchronizeddisplay of discourse segments, topic stamps, and relational contexts inthree panels. The whole document 816 is displayed in the left panel;this is deliberately unreadable, and is intended to function as adocument thumbnail serving as a contextual referent for the topicspresented in the central panel. With the use of an appropriate colorcoding scheme, it also serves as an indicator of the distribution oftopically prominent phrases in the document. The central panel 804 liststhe highly salient topic stamps. Contextualization for these is achievedby aligning the topic stamps for a given discourse segment with thetextual span of that segment in the thumbnail as indicated by 808 and810 in FIG. 8A and discussed below. This offers an immediate overviewof, for instance, what is being discussed in the beginning of thedocument, or in the end, or which topics keep recurring throughout, andso forth.

The central panel is sensitive to the user's focus of attention: as themouse rolls over a topic stamp 804, the discourse segment from whichthis topic has been extracted is highlighted in the left panel shown at810. The highlighting also indicates the segmentation of the sourcedocuments into topically different, and distinct, text sections. Thisdesign makes it easy to do rapid selection of areas of interest in thedocument, as it is mediated by the topic stamps per segment display.Again, the granularity of analysis and the layered contextualinformation in the capsule overview make it easy to offer immediate andmore detailed information about any given set of topic stamps:simultaneously with highlighting the appropriate discourse segment 810in the left panel 802, relational contexts for the same set of topicstamps 808 and 812 are displayed cyclically, in RSVP-like fashion 814,in the right panel 806. This ensures that topic stamps are alwaysrelated with contextual cue phrases. Thus an additional level of detailis made available to the user, with very little ‘prompting’ on theirpart. On the other hand, as FIG. 8B illustrates, if it is still the casethat the full text of the segment would be required, clicking on its‘proxy’ topic stamps 808 (in the middle panel) would display this in theright panel 818. The larger area available there, as well as anautomatic readjustment of the size of type, ensures that the text isreadable.

Referring now to FIG. 8C, as a natural extension of the same metaphor,clicking on the document proxy 816 in the left panel brings up the fulldocument text in the right panel 820. The full text always uses colormarkup to indicate, in yet another way, topically salient phrases andtheir relational contexts.

By always maintaining the larger document context for any grain ofinformation of relevance and interest in the documents, ViewTool vieweris an ideal skimming tool, because it provides additional informationthat may be important in deciding whether looking more closely at thedocument would be required. For example, users can get a sense of thesize of the document, whether it contains any pictures, and other visualcue features. They can see the density of topics and the relevantordering of the topics in relation to the different sections of thedocument. The tool offers the ability to see arbitrarily detailedcontextual information relevant to a topic, while leveraging that samecontainment hierarchy of layered information units to prevent overload.

8S. Viewer's Summary

The viewers in a preferred embodiment can be fully implemented in Javafor cross-platform use, and can be deployed in a variety of ways withina suite of intranet tools for collaboration and communication withincommunities. In one particular example of use, an on-line newspaper hasbeen configured as the primary news source within a learning community.By means of a variety of web spiders and document filters, external newsstories are collected and ‘published’ in the newspaper. RSVP is used forprimary delivery of the external news, on a dedicated page, projected onlarge display in a shared common area. TopicsTicker Viewer offers abrief overview of the latest news on the front page of the newspaper.ViewTool Viewer is available as an alternative browser, for morepro-active and focused access to the document particularly in situationswhere the newspaper is being viewed in personal workstations. ViewToolViewer is also used for browsing of personal information, feeds, sent toa document analysis server engine via a simple e-mail protocol. Ingeneral, any configuration of viewers can be deployed for personalized‘windows’ into continuous news feeds, combining a variety of screendelivery modes.

The notions of temporal typography and dynamic delivery of contentmediated via content highlights offer an appealing synergy of form andcontent, which not only alleviates inevitable (given the currentstate-of-the-art of text processing technology) shortcomings ofsummarization technologies today, but also suggests that additionalutility, and user satisfaction, can be derived from imperfect analysistechnologies—if usability and interface issues are addressed from thisperspective.

A system and method in accordance with the present invention isdisclosed which can present thematic capsule overviews of documents tousers. For each document a capsule overview is derived which will depictthe core content of an average length article in a more accurate andrepresentative manner than utilizing conventional techniques. Thecapsule overviews, delivered in a variety of dynamic presentation modes,allow the user to quickly get a sense of what a document is about, anddecide whether they want to read it in more detail. Thus, the system andmethod greatly facilitate the process of focused navigation into theparts of the document which may be of particular interest to the user.In a preferred embodiment the display of capsule overviews leveragenovel presentation metaphors for the dynamic delivery of content. Thisdelivery can be mediated by multilayered abstractions of documentcontent, making heavy use of ideas of temporal typography, in particularfor exploiting the interactions between form and content.

Although the present invention has been described in accordance with theembodiments shown, one of ordinary skill in the art will readilyrecognize that there could be variations to the embodiments and thosevariations would be within the spirit and scope of the presentinvention. Accordingly, many modifications may be made by one ofordinary skill in the art without departing from the spirit and scope ofthe appended claims.

What is claimed is:
 1. A computer readable medium containing programminginstructions for dynamically presenting the contents of a plurality ofdocuments on a display, the programming instructions for: a) receiving aplurality of documents; b) generating a plurality of capsule overviewscorresponding to the plurality of documents by utilizing the followinginstructions for each document: 1) identifying a plurality of discoursereferents in the document; 2) dividing the document into topicallyrelevant document segments; 3) resolving co-referentiality among thediscourse referents within, and across, the document segments, whereinthe resolving step comprises linking the discourse referents byco-referentiality with each other to assess a frequency with which theyappear within the document and to establish prominence; 4) calculatingdiscourse salience values for the discourse referents based upon theresolving step; 5) determining topic stamps for each of the documentsegments based upon discourse salience values of the associateddiscourse referents; and 6) providing a capsule overview of thedocument, constructed from the topic stamps; and c) dynamicallydelivering document content as encapsulated within the plurality ofcapsule overviews.
 2. The computer readable medium of claim 1 whereinthe plurality of capsule overviews include a containment hierarchy. 3.The computer readable medium of claim 2 wherein the containmenthierarchy of information-bearing units provides different levels ofabstractions of the document.
 4. The computer readable medium of claim 3wherein the abstractions comprise at least one topic stamp which isembedded within a plurality of layers of progressively more informativetext fragments related to the document.
 5. The computer readable mediumof claim 4 wherein the discourse salience values are indicative of therelative importance of the discourse referents.
 6. The computer readablemedium of claim 5 wherein the document content is delivered via aTopicsTicker viewer.
 7. The computer readable medium of claim 2, whereinthe containment hierarchy is accessed automatically.
 8. The computerreadable medium of claim 7 wherein the document content is delivered viaa Rapid Serial Visual Presentation viewer.
 9. The computer readablemedium of claim 8 wherein the instruction for delivering documentcontent (c) further includes the programming instructions for: (c1)cycling through a plurality of topic stamps and their associatedrelational contexts for the plurality of documents.
 10. The computerreadable medium of claim 9 wherein the instruction for cycling (c1)further includes instructions for: (c1i) selecting a document from theplurality of documents; (c1ii) selecting a topic stamp from the documentfrom the capsule overview; (c1iii) selecting a relational contextrelating to the topic stamp from the capsule overview; (c1iv) retrievinga canonical form of the topic stamp from the capsule overview; (c1v)displaying the topic stamp in background and the relational context inthe foreground for a time period that is calculated automatically; and(c1vi) repeating steps (c1i)-(c1v) for the plurality of documents. 11.The computer readable medium of claim 10 wherein the topic stamp andrelational context zoom in and out.
 12. The computer readable medium ofclaim 10 wherein the time period for display is calculated based onamount of the relational context.
 13. The computer readable medium ofclaim 12 wherein the topic stamp and relational context are displayed atdifferent intensities.
 14. The computer readable medium of claim 13wherein the topic stamp is dark and relational context is translucent.15. The computer readable medium of claim 7 wherein the document contentis delivered via a ViewTool viewer.
 16. The computer readable medium ofclaim 2 wherein the containment hierarchy is accessed manually.
 17. Thecomputer readable medium of claim 16 wherein the document content isdelivered via a Rapid Serial Visual Presentation viewer.
 18. Thecomputer readable medium of claim 16 wherein the document content isdelivered via a ViewTool viewer.
 19. The computer readable medium ofclaim 1 wherein the data is displayed via a screen saver.
 20. Thecomputer readable medium of claim 1 wherein the data is displayed on alarge screen projection.
 21. The computer readable medium of claim 1wherein the data is displayed in a background window on a computer. 22.A system for dynamically presenting the contents of a plurality ofdocuments on a display, comprising: means for receiving a plurality ofdocuments; a memory for storing the plurality of documents; a processorcoupled to the memory functioning to generate a plurality of capsuleoverviews corresponding to the plurality of documents, wherein, for eachdocument, the processor identifies a plurality of discourse referents inthe document, divides the document into topically relevant documentsegments, resolves co-referentiality among the discourse referentswithin, and across, the document segments, calculates discourse saliencevalues for the discourse referents based upon the resolving, determinestopic stamps for each of the document segments based upon discoursesalience values of the associated discourse referents, and provides acapsule overview of the document, constructed from the topic stamps; anda display for delivering document content as encapsulated within theplurality of capsule overviews.
 23. The system of claim 22, wherein theplurality of capsule overviews include a containment hierarchy.
 24. Thesystem of claim 23, wherein the containment hierarchy ofinformation-bearing units provides different levels of abstractions ofthe document.
 25. The system of claim 24, wherein the abstractionscomprise at least one topic stamp which is embedded within a pluralityof layers of progressively more informative text fragments related tothe document.
 26. The system of claim 25, wherein the discourse saliencevalues are indicative of the relative importance of the discoursereferents.
 27. The system of claim 26, wherein the display delivers thedocument content via a TopicsTicker viewer.
 28. The system of claim 23,wherein the containment hierarchy is accessed automatically.
 29. Thesystem of claim 28, wherein the display delivers the document contentvia a Rapid Serial Visual Presentation viewer.
 30. The system of claim29, wherein the Rapid Serial Visual Presentation viewer cycles through aplurality of topic stamps and their associated relational contexts forthe plurality of documents.
 31. The system of claim 28, wherein thedisplay delivers the document content via a ViewTool viewer.
 32. Thesystem of claim 22, wherein the document content is delivered via ascreen saver.
 33. The system of claim 22, wherein the document contentis delivered via a background window on a computer.
 34. The system ofclaim 22, wherein the system is a computer system in communication witha plurality of electronic devices via a network.
 35. The system of claim22, wherein the system is a server in communication with a plurality ofclient systems via a network.
 36. A method for dynamically presentingthe contents of a plurality of documents on a display, the methodcomprising the steps of: a) receiving a plurality of documents; b)generating a plurality of capsule overviews corresponding to theplurality of documents, wherein the generating step further includes thesteps of: 1) identifying a plurality of discourse referents in thedocument; 2) dividing the document into topically relevant documentsegments; and 3) for each discourse referent, linking the discoursereferent by co-referentiality to each other within, and across, thedocument segments to assess a frequency with which it appears within thedocument thereby determining prominence of the discourse referent; andc) dynamically delivering document content as encapsulated within theplurality of capsule overviews.
 37. The method of claim 36, wherein thegenerating step (b) further includes the steps of: 4) calculatingdiscourse salience values for the discourse referents based upon thelinking step; 5) determining topic stamps for each of the documentsegments based upon discourse salience values of the associateddiscourse referents; and 6) providing a capsule overview of thedocument, constructed from the topic stamps.
 38. The method of claim 37,wherein the plurality of capsule overviews include a containmenthierarchy.
 39. The method of claim 38, wherein the containment hierarchyof information-bearing units provides different levels of abstractionsof the document.
 40. The method of claim 39, wherein the abstractionscomprise at least one topic stamp which is embedded within a pluralityof layers of progressively more informative text fragments related tothe document.
 41. The method of claim 40, wherein the discourse saliencevalues are indicative of the relative importance of the discoursereferents.
 42. A computer readable medium containing programminginstructions for dynamically presenting the contents of a plurality ofdocuments on a display, the programming instructions for: a) receiving aplurality of documents; b) generating a plurality of capsule overviewscorresponding to the plurality of documents, wherein the generatinginstructions further include the instructions for: 1) identifying aplurality of discourse referents in the document; 2) dividing thedocument into topically relevant document segments; and 3) for eachdiscourse referent, linking the discourse referent by co-referentialityto each other within, and across, the document segments to assess afrequency with which it appears within the document thereby determiningprominence of the discourse referent; and c) dynamically deliveringdocument content as encapsulated within the plurality of capsuleoverviews.
 43. The computer readable medium of claim 42, wherein thegenerating instruction (b) further includes instructions for: 4)calculating discourse salience values for the discourse referents basedupon the linking step; 5) determining topic stamps for each of thedocument segments based upon discourse salience values of the associateddiscourse referents; and 6) providing a capsule overview of thedocument, constructed from the topic stamps.
 44. The computer readablemedium of claim 43, wherein the plurality of capsule overviews include acontainment hierarchy.
 45. The computer readable medium of claim 44,wherein the containment hierarchy of information-bearing units providesdifferent levels of abstractions of the document.
 46. The computerreadable medium of claim 45, wherein the abstractions comprise at leastone topic stamp which is embedded within a plurality of layers ofprogressively more informative text fragments related to the document.47. The computer readable medium of claim 46, wherein the discoursesalience values are indicative of the relative importance of thediscourse referents.